Precision machine vision inspection systems (or “vision systems” for short) can be utilized to obtain precise dimensional measurements of inspected objects and to inspect various other object characteristics. Such systems may include a computer, a camera and optical system, and a precision stage that is movable in multiple directions so as to allow the camera to scan the features of a workpiece that is being inspected. One exemplary prior art system that is commercially available is the QUICK VISION® series of PC-based vision systems and QVPAK® software available from Mitutoyo America Corporation (MAC), located in Aurora, Ill. The features and operation of the QUICK VISION® series of vision systems and the QVPAK® software are generally described, for example, in the QVPAK 3D CNC Vision Measuring Machine User's Guide, published January 2003, and the QVPAK 3D CNC Vision Measuring Machine Operation Guide, published September 1996, each of which is hereby incorporated by reference in their entirety. This product, as exemplified by the QV-302 Pro model, for example, is able to use a microscope-type optical system to provide images of a workpiece at various magnifications, and move the stage as necessary to traverse the workpiece surface beyond the limits of any single video image. A single video image typically encompasses only a portion of the workpiece being observed or inspected, given the desired magnification, measurement resolution, and physical size limitations of such systems.
Machine vision inspection systems generally utilize automated video inspection. U.S. Pat. No. 6,542,180 (the '180 patent) teaches various aspects of such automated video inspection and is incorporated herein by reference in its entirety. As taught in the '180 patent, automated video inspection metrology instruments generally have a programming capability that allows an automatic inspection event sequence to be defined by the user for each particular workpiece configuration. This can be implemented by text-based programming, for example, or through a recording mode which progressively “learns” the inspection event sequence by storing a sequence of machine control instructions corresponding to a sequence of inspection operations performed by a user with the aid of a graphical user interface, or through a combination of both methods. Such a recording mode is often referred to as “learn mode” or “training mode.” Once the inspection event sequence is defined in “learn mode,” such a sequence can then be used to automatically acquire (and additionally analyze or inspect) images of a workpiece during “run mode.”
The machine control instructions including the specific inspection event sequence (i.e., how to acquire each image and how to analyze/inspect each acquired image) are generally stored as a “part program” or “workpiece program” that is specific to the particular workpiece configuration. For example, a part program defines how to acquire each image, such as how to position the camera relative to the workpiece, at what lighting level, at what magnification level, etc. Further, the part program defines how to analyze/inspect an acquired image, for example, by using one or more video tools such as edge/boundary detection video tools.
Video tools (or “tools” for short) and other graphical user interface features may be used manually to accomplish manual inspection and/or machine control operations (in “manual mode”). Their set-up parameters and operation can also be recorded during learn mode, in order to create automatic inspection programs, or “part programs.” Video tools may include, for example, edge/boundary detection tools, autofocus tools, shape or pattern matching tools, dimension measuring tools, and the like.
One application for a machine vision inspection system is the inspection of features on a workpiece. In some cases, these features may be contained in different layers and/or may interfere or have overlapping edges. One example of such a workpiece is a printed circuit board (PCB), wherein it may be desirable to measure the registration relationship between a pattern in a solder resist layer and conductive features intended to be exposed and/or insulated by the solder resist layer. Such features may be concentric, or in some cases, fabrication errors may occur which cause the edges of some of the features to overlap or interfere. Such errors may be associated with short circuiting or other problems for the operation of the PCB. Thus, during the inspection of the PCB, it is important to be able to accurately determine if the features are properly located. However, prior art methods for automatically inspecting such features are neither easy enough to program for unskilled users of the machine vision inspection system, nor robust enough to operate properly under a wide variety of possible alignments and misalignment conditions for the related features, which may potentially not overlap, or overlap to various degrees. Improvements in programming and techniques related to accurately detecting and/or measuring potentially overlapping or interfering features on workpieces such as PCBs, would be desirable.